This invention relates generally to methods and apparatus for computed tomography (CT), and more particularly to methods and apparatus for noise estimation in CT.
Noise reduction has been the focus of research for x-ray computed tomography (CT) for many years. The goal of noise reduction is not only to improve the visibility of low-contrast objects, but also to reduce the x-ray dose to patients without sacrificing image quality. It is well known that noise reduction can be performed either in the projection space or in the image space. There are pros and cons with either approach. In this patent, we describe an image space filtration approach that significantly improves the noise characteristics of the resulting images.
In recent years, several authors presented reduction methods based on anisotropic diffusion and nonlinear processing of wavelet coefficients. Wavelet based methods can be implemented efficiently. However, traditional wavelet based noise suppression techniques are known to introduce artifacts, such as ringing, near sharp transitions in the image.
Accordingly, an improvement of the original algorithm using a multi-scale version of the anisotropic diffusion is desirable. And using a Dyadic Wavelet scheme to decompose the image into different image scales is also desirable.